• Continuing with the last project theme, I will do a quick analysis of my climbing stats
• I will look at the distribution of 2 variables: elevation (how tall a peak is) and prominence (height of a peak relative to its surroundings) using a histogram
• Both histograms shown in this project were made using Plotly (code is included on the slides) and can be found on slides 7 and 8

On the summit of Big Snagtooth

##       lat             lng              name             elevation    
##  Min.   :20.53   Min.   :-123.26   Length:94          Min.   :   66  
##  1st Qu.:47.42   1st Qu.:-121.99   Class :character   1st Qu.: 1890  
##  Median :47.62   Median :-121.54   Mode  :character   Median : 6690  
##  Mean   :46.53   Mean   :-116.53                      Mean   : 5524  
##  3rd Qu.:48.23   3rd Qu.:-120.61                      3rd Qu.: 8373  
##  Max.   :48.89   Max.   :  13.06                      Max.   :12276  
##    prominence    
##  Min.   :   0.0  
##  1st Qu.: 125.8  
##  Median : 473.0  
##  Mean   :1002.9  
##  3rd Qu.:1164.8  
##  Max.   :8812.0

• The map in the following slide was made using the code from the previous assignment
• Code available in https://github.com/honvales/DataProductsProject2

## Assuming "lng" and "lat" are longitude and latitude, respectively

plot_ly(x = el, type='histogram')

plot_ly(x = pr, type='histogram')

• Most of the peaks that I have climbed have elevations above 8000 ft or below 1000 ft (thanks COVID)
• Most of the peaks that I climb have a prominence below 1000 ft